Volunteer Summary - MMH

CONSORT map

Demographic information

Characteristic

N = 281

age

42.28 ± 14.85 (21 - 70)

gender

female

24 (86%)

male

4 (14%)

occupation

civil

1 (3.6%)

clerk

6 (21%)

homemaker

5 (18%)

manager

3 (11%)

other

3 (11%)

professional

3 (11%)

retired

2 (7.1%)

service

1 (3.6%)

student

3 (11%)

unemploy

1 (3.6%)

marital

divorced

2 (7.1%)

married

9 (32%)

single

17 (61%)

education

primary

0 (0%)

secondary

7 (25%)

post-secondary

3 (11%)

university

18 (64%)

family_income

0_10000

4 (14%)

10001_20000

6 (21%)

20001_30000

4 (14%)

30001_40000

5 (18%)

40000_above

9 (32%)

religion

buddhism

1 (3.6%)

catholic

3 (11%)

christianity

9 (32%)

nil

13 (46%)

other

1 (3.6%)

taoism

1 (3.6%)

source

bokss

14 (50%)

facebook

2 (7.1%)

other

6 (21%)

refresh

6 (21%)

previous_volunteer

yes_beyong_12_month

12 (43%)

yes_within_12_month

16 (57%)

previous_volunteer_r

yes

28 (100%)

current_volunteer

no

11 (39%)

yes

17 (61%)

number_volunteer_r

1.00 ± 1.05 (0 - 3)

1Mean ± SD (Range); n (%)

Measurement

Characteristic

1st, N = 281

2nd, N = 271

sets

19.75 ± 2.20 (15 - 25)

19.52 ± 2.23 (14 - 25)

setv

11.11 ± 1.71 (8 - 15)

11.30 ± 1.88 (7 - 15)

maks

44.25 ± 3.50 (38 - 54)

44.93 ± 3.86 (36 - 54)

ibs

15.36 ± 2.08 (9 - 20)

15.93 ± 1.41 (13 - 20)

ers_e

12.25 ± 1.04 (10 - 15)

12.26 ± 1.26 (10 - 15)

ers_r

11.29 ± 1.44 (8 - 15)

11.52 ± 1.42 (9 - 15)

pss_pa

45.36 ± 4.42 (31 - 53)

44.19 ± 3.93 (36 - 50)

pss_ps

24.43 ± 6.61 (12 - 41)

24.15 ± 6.86 (13 - 38)

pss

42.07 ± 10.23 (24 - 67)

42.96 ± 10.07 (27 - 61)

rki_responsible

21.39 ± 3.07 (14 - 27)

21.30 ± 3.35 (16 - 28)

rki_nonlinear

13.29 ± 2.27 (8 - 17)

13.67 ± 3.15 (7 - 20)

rki_peer

19.96 ± 1.99 (17 - 25)

20.33 ± 2.27 (15 - 25)

rki_expect

4.86 ± 1.04 (3 - 7)

5.07 ± 1.11 (3 - 8)

rki

59.50 ± 4.16 (52 - 67)

60.37 ± 5.25 (51 - 70)

raq_possible

15.21 ± 1.69 (12 - 20)

15.70 ± 1.54 (12 - 19)

raq_difficulty

12.11 ± 1.52 (9 - 15)

12.33 ± 1.36 (9 - 15)

raq

27.32 ± 3.03 (21 - 35)

28.04 ± 2.81 (21 - 34)

who

15.39 ± 4.35 (8 - 25)

15.11 ± 4.63 (9 - 25)

phq

3.57 ± 3.95 (0 - 18)

3.41 ± 3.47 (0 - 14)

gad

2.93 ± 3.21 (0 - 12)

3.15 ± 3.00 (0 - 10)

nb_pcs

47.93 ± 8.57 (27 - 61)

50.51 ± 6.53 (34 - 58)

nb_mcs

52.30 ± 8.20 (35 - 70)

51.33 ± 6.41 (36 - 65)

1Mean ± SD (Range)

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

sets

(Intercept)

21.8

2.306

17.3, 26.3

age

-0.032

0.029

-0.090, 0.025

0.289

gender

female

—

—

—

male

0.662

0.995

-1.29, 2.61

0.514

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.693

0.777

-0.831, 2.22

0.384

number_volunteer_r

0.623

0.487

-0.332, 1.58

0.209

attendance

-0.359

0.391

-1.13, 0.408

0.372

time_point

1st

—

—

—

2nd

0.520

0.798

-1.04, 2.08

0.520

Pseudo R square

0.178

setv

(Intercept)

13.6

2.087

9.53, 17.7

age

-0.011

0.027

-0.063, 0.042

0.692

gender

female

—

—

—

male

0.767

0.906

-1.01, 2.54

0.409

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.543

0.701

-1.92, 0.830

0.449

number_volunteer_r

0.505

0.331

-0.143, 1.15

0.137

attendance

-0.494

0.357

-1.19, 0.206

0.186

time_point

1st

—

—

—

2nd

1.01

0.507

0.012, 2.00

0.059

Pseudo R square

0.156

maks

(Intercept)

45.3

5.060

35.4, 55.2

age

0.053

0.065

-0.076, 0.181

0.432

gender

female

—

—

—

male

2.26

2.203

-2.06, 6.58

0.319

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-1.37

1.693

-4.68, 1.95

0.430

number_volunteer_r

-0.399

0.573

-1.52, 0.725

0.493

attendance

-0.488

0.870

-2.19, 1.22

0.582

time_point

1st

—

—

—

2nd

0.366

0.851

-1.30, 2.03

0.671

Pseudo R square

0.087

ibs

(Intercept)

17.5

1.839

13.9, 21.1

age

0.010

0.024

-0.036, 0.056

0.680

gender

female

—

—

—

male

-1.62

0.798

-3.18, -0.056

0.057

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-1.23

0.617

-2.44, -0.020

0.061

number_volunteer_r

0.125

0.299

-0.462, 0.711

0.680

attendance

-0.368

0.315

-0.985, 0.248

0.257

time_point

1st

—

—

—

2nd

1.04

0.460

0.141, 1.94

0.032

Pseudo R square

0.298

ers_e

(Intercept)

13.0

1.427

10.2, 15.8

age

-0.003

0.018

-0.039, 0.033

0.871

gender

female

—

—

—

male

-0.630

0.621

-1.85, 0.587

0.324

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.040

0.478

-0.978, 0.897

0.934

number_volunteer_r

0.434

0.187

0.068, 0.800

0.028

attendance

-0.152

0.245

-0.633, 0.328

0.542

time_point

1st

—

—

—

2nd

0.497

0.280

-0.053, 1.05

0.089

Pseudo R square

0.095

ers_r

(Intercept)

13.2

1.609

10.0, 16.3

age

0.007

0.021

-0.034, 0.047

0.743

gender

female

—

—

—

male

-0.839

0.697

-2.21, 0.528

0.245

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.115

0.541

-0.945, 1.18

0.834

number_volunteer_r

0.190

0.284

-0.367, 0.748

0.508

attendance

-0.434

0.275

-0.972, 0.105

0.132

time_point

1st

—

—

—

2nd

0.460

0.444

-0.410, 1.33

0.310

Pseudo R square

0.122

pss_pa

(Intercept)

46.3

4.666

37.1, 55.4

age

0.031

0.060

-0.086, 0.149

0.606

gender

female

—

—

—

male

-3.89

2.024

-7.86, 0.074

0.070

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-1.11

1.568

-4.19, 1.96

0.487

number_volunteer_r

0.295

0.790

-1.25, 1.84

0.711

attendance

-0.346

0.798

-1.91, 1.22

0.669

time_point

1st

—

—

—

2nd

0.177

1.222

-2.22, 2.57

0.886

Pseudo R square

0.151

pss_ps

(Intercept)

17.0

8.020

1.28, 32.7

age

0.005

0.104

-0.198, 0.208

0.962

gender

female

—

—

—

male

2.01

3.492

-4.83, 8.86

0.572

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

5.20

2.683

-0.055, 10.5

0.068

number_volunteer_r

-1.40

0.878

-3.12, 0.317

0.122

attendance

1.08

1.380

-1.63, 3.78

0.446

time_point

1st

—

—

—

2nd

-3.33

1.300

-5.88, -0.786

0.017

Pseudo R square

0.162

pss

(Intercept)

33.7

12.025

10.2, 57.3

age

-0.026

0.155

-0.331, 0.278

0.867

gender

female

—

—

—

male

5.90

5.233

-4.36, 16.2

0.274

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

6.31

4.026

-1.58, 14.2

0.134

number_volunteer_r

-1.69

1.452

-4.53, 1.16

0.256

attendance

1.42

2.067

-2.63, 5.47

0.500

time_point

1st

—

—

—

2nd

-3.50

2.165

-7.74, 0.744

0.119

Pseudo R square

0.147

rki_responsible

(Intercept)

17.1

2.830

11.5, 22.6

age

-0.054

0.036

-0.125, 0.017

0.154

gender

female

—

—

—

male

-2.39

1.222

-4.79, 0.004

0.066

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.913

0.954

-0.956, 2.78

0.350

number_volunteer_r

-0.378

0.582

-1.52, 0.762

0.520

attendance

1.39

0.481

0.451, 2.34

0.010

time_point

1st

—

—

—

2nd

-0.482

0.943

-2.33, 1.37

0.614

Pseudo R square

0.262

rki_nonlinear

(Intercept)

12.2

3.293

5.75, 18.7

age

-0.046

0.042

-0.129, 0.037

0.288

gender

female

—

—

—

male

-0.767

1.428

-3.57, 2.03

0.598

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.317

1.106

-2.49, 1.85

0.778

number_volunteer_r

-0.305

0.555

-1.39, 0.782

0.586

attendance

0.710

0.563

-0.393, 1.81

0.223

time_point

1st

—

—

—

2nd

0.029

0.858

-1.65, 1.71

0.973

Pseudo R square

0.092

rki_peer

(Intercept)

21.6

2.611

16.5, 26.7

age

-0.012

0.034

-0.078, 0.054

0.724

gender

female

—

—

—

male

-0.778

1.132

-3.00, 1.44

0.501

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.120

0.877

-1.60, 1.84

0.893

number_volunteer_r

0.434

0.444

-0.435, 1.30

0.335

attendance

-0.325

0.446

-1.20, 0.550

0.476

time_point

1st

—

—

—

2nd

1.11

0.687

-0.241, 2.45

0.119

Pseudo R square

0.071

rki_expect

(Intercept)

5.29

1.194

2.95, 7.63

age

-0.026

0.015

-0.055, 0.004

0.113

gender

female

—

—

—

male

0.106

0.516

-0.906, 1.12

0.840

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.508

0.402

-1.30, 0.280

0.222

number_volunteer_r

-0.033

0.233

-0.489, 0.423

0.888

attendance

0.184

0.203

-0.215, 0.582

0.379

time_point

1st

—

—

—

2nd

0.270

0.371

-0.458, 0.997

0.473

Pseudo R square

0.138

rki

(Intercept)

56.2

4.440

47.5, 64.9

age

-0.138

0.057

-0.249, -0.026

0.026

gender

female

—

—

—

male

-3.82

1.920

-7.59, -0.058

0.062

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.222

1.495

-2.71, 3.15

0.883

number_volunteer_r

-0.320

0.859

-2.00, 1.36

0.712

attendance

1.96

0.756

0.481, 3.44

0.018

time_point

1st

—

—

—

2nd

0.884

1.367

-1.80, 3.56

0.523

Pseudo R square

0.290

raq_possible

(Intercept)

14.6

1.852

11.0, 18.3

age

-0.009

0.024

-0.055, 0.038

0.717

gender

female

—

—

—

male

-1.08

0.802

-2.65, 0.491

0.195

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.844

0.623

-0.377, 2.06

0.192

number_volunteer_r

0.053

0.327

-0.588, 0.694

0.872

attendance

0.166

0.316

-0.454, 0.785

0.607

time_point

1st

—

—

—

2nd

0.273

0.510

-0.727, 1.27

0.598

Pseudo R square

0.102

raq_difficulty

(Intercept)

10.6

1.769

7.12, 14.1

age

-0.007

0.023

-0.052, 0.038

0.765

gender

female

—

—

—

male

-0.498

0.768

-2.00, 1.01

0.524

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.530

0.594

-0.634, 1.70

0.383

number_volunteer_r

0.106

0.290

-0.462, 0.675

0.716

attendance

0.312

0.303

-0.281, 0.905

0.316

time_point

1st

—

—

—

2nd

0.241

0.447

-0.634, 1.12

0.594

Pseudo R square

0.066

raq

(Intercept)

25.2

3.527

18.3, 32.2

age

-0.016

0.045

-0.104, 0.073

0.736

gender

female

—

—

—

male

-1.57

1.530

-4.57, 1.43

0.318

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

1.39

1.184

-0.936, 3.71

0.257

number_volunteer_r

0.129

0.571

-0.989, 1.25

0.823

attendance

0.478

0.604

-0.705, 1.66

0.439

time_point

1st

—

—

—

2nd

0.483

0.877

-1.24, 2.20

0.587

Pseudo R square

0.085

who

(Intercept)

17.4

5.797

6.05, 28.8

age

-0.073

0.075

-0.220, 0.074

0.344

gender

female

—

—

—

male

-1.11

2.523

-6.05, 3.84

0.666

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.852

1.941

-4.66, 2.95

0.666

number_volunteer_r

0.432

0.715

-0.969, 1.83

0.551

attendance

0.160

0.996

-1.79, 2.11

0.874

time_point

1st

—

—

—

2nd

0.625

1.067

-1.47, 2.72

0.564

Pseudo R square

0.043

phq

(Intercept)

-2.57

4.956

-12.3, 7.14

age

0.024

0.064

-0.102, 0.149

0.716

gender

female

—

—

—

male

0.553

2.160

-3.68, 4.79

0.801

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

1.51

1.656

-1.74, 4.76

0.374

number_volunteer_r

-0.466

0.456

-1.36, 0.428

0.318

attendance

0.887

0.854

-0.786, 2.56

0.313

time_point

1st

—

—

—

2nd

-0.356

0.671

-1.67, 0.959

0.601

Pseudo R square

0.076

gad

(Intercept)

0.693

4.105

-7.35, 8.74

age

-0.002

0.053

-0.106, 0.102

0.971

gender

female

—

—

—

male

2.37

1.789

-1.13, 5.88

0.202

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.637

1.372

-2.05, 3.33

0.648

number_volunteer_r

-0.213

0.398

-0.993, 0.566

0.597

attendance

0.366

0.707

-1.02, 1.75

0.611

time_point

1st

—

—

—

2nd

0.212

0.586

-0.936, 1.36

0.721

Pseudo R square

0.089

nb_pcs

(Intercept)

65.5

5.616

54.5, 76.5

age

-0.290

0.072

-0.431, -0.150

0.001

gender

female

—

—

—

male

-1.38

2.426

-6.13, 3.38

0.578

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

0.466

1.892

-3.24, 4.17

0.808

number_volunteer_r

2.11

1.139

-0.118, 4.34

0.071

attendance

-1.13

0.955

-3.00, 0.739

0.254

time_point

1st

—

—

—

2nd

3.98

1.838

0.376, 7.58

0.040

Pseudo R square

0.428

nb_mcs

(Intercept)

53.2

8.805

36.0, 70.5

age

0.036

0.113

-0.186, 0.259

0.752

gender

female

—

—

—

male

-2.08

3.825

-9.58, 5.41

0.593

previous_volunteer

yes_beyong_12_month

—

—

—

yes_within_12_month

-0.974

2.954

-6.76, 4.82

0.746

number_volunteer_r

0.179

1.327

-2.42, 2.78

0.893

attendance

-0.470

1.509

-3.43, 2.49

0.759

time_point

1st

—

—

—

2nd

-0.296

2.018

-4.25, 3.66

0.885

Pseudo R square

0.024

1SE = Standard Error, CI = Confidence Interval

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: sets ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.31) and the part related to the fixed effects alone (marginal R2) is of 0.18. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 21.79 (S.E. = 2.31, p < .001, 95% CI [17.27, 26.31]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.03, S.E. = 0.03, p = 0.274, 95% CI [-0.09, 0.03]; Std. beta = -0.18, 95% CI [-0.51, 0.14])
  • The effect of gender [male] is statistically non-significant and positive (beta = 0.66, S.E. = 0.99, p = 0.505, 95% CI [-1.29, 2.61]; Std. beta = 0.28, 95% CI [-0.55, 1.11])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.69, S.E. = 0.78, p = 0.373, 95% CI [-0.83, 2.22]; Std. beta = 0.29, 95% CI [-0.35, 0.94])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.62, S.E. = 0.49, p = 0.201, 95% CI [-0.33, 1.58]; Std. beta = 0.23, 95% CI [-0.12, 0.59])
  • The effect of attendance is statistically non-significant and negative (beta = -0.36, S.E. = 0.39, p = 0.359, 95% CI [-1.13, 0.41]; Std. beta = -0.15, 95% CI [-0.48, 0.17])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.52, S.E. = 0.80, p = 0.515, 95% CI [-1.04, 2.08]; Std. beta = 0.22, 95% CI [-0.44, 0.88])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: setv ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.16. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 13.62 (S.E. = 2.09, p < .001, 95% CI [9.53, 17.71]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.01, S.E. = 0.03, p = 0.687, 95% CI [-0.06, 0.04]; Std. beta = -0.08, 95% CI [-0.45, 0.30])
  • The effect of gender [male] is statistically non-significant and positive (beta = 0.77, S.E. = 0.91, p = 0.397, 95% CI [-1.01, 2.54]; Std. beta = 0.41, 95% CI [-0.53, 1.35])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.54, S.E. = 0.70, p = 0.438, 95% CI [-1.92, 0.83]; Std. beta = -0.29, 95% CI [-1.02, 0.44])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.51, S.E. = 0.33, p = 0.127, 95% CI [-0.14, 1.15]; Std. beta = 0.24, 95% CI [-0.07, 0.54])
  • The effect of attendance is statistically non-significant and negative (beta = -0.49, S.E. = 0.36, p = 0.167, 95% CI [-1.19, 0.21]; Std. beta = -0.26, 95% CI [-0.63, 0.11])
  • The effect of time point [2nd] is statistically significant and positive (beta = 1.01, S.E. = 0.51, p = 0.047, 95% CI [0.01, 2.00]; Std. beta = 0.53, 95% CI [6.53e-03, 1.06])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: maks ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.09. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 45.31 (S.E. = 5.06, p < .001, 95% CI [35.40, 55.23]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 0.05, S.E. = 0.07, p = 0.422, 95% CI [-0.08, 0.18]; Std. beta = 0.18, 95% CI [-0.26, 0.62])
  • The effect of gender [male] is statistically non-significant and positive (beta = 2.26, S.E. = 2.20, p = 0.305, 95% CI [-2.06, 6.58]; Std. beta = 0.58, 95% CI [-0.53, 1.70])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -1.37, S.E. = 1.69, p = 0.420, 95% CI [-4.68, 1.95]; Std. beta = -0.35, 95% CI [-1.21, 0.50])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.40, S.E. = 0.57, p = 0.487, 95% CI [-1.52, 0.72]; Std. beta = -0.09, 95% CI [-0.35, 0.17])
  • The effect of attendance is statistically non-significant and negative (beta = -0.49, S.E. = 0.87, p = 0.575, 95% CI [-2.19, 1.22]; Std. beta = -0.13, 95% CI [-0.57, 0.31])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.37, S.E. = 0.85, p = 0.667, 95% CI [-1.30, 2.03]; Std. beta = 0.09, 95% CI [-0.34, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: ibs ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.30. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 17.54 (S.E. = 1.84, p < .001, 95% CI [13.93, 21.14]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 9.93e-03, S.E. = 0.02, p = 0.675, 95% CI [-0.04, 0.06]; Std. beta = 0.07, 95% CI [-0.27, 0.42])
  • The effect of gender [male] is statistically significant and negative (beta = -1.62, S.E. = 0.80, p = 0.042, 95% CI [-3.18, -0.06]; Std. beta = -0.90, 95% CI [-1.76, -0.03])
  • The effect of previous volunteer [yes_within_12_month] is statistically significant and negative (beta = -1.23, S.E. = 0.62, p = 0.046, 95% CI [-2.44, -0.02]; Std. beta = -0.68, 95% CI [-1.35, -0.01])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.12, S.E. = 0.30, p = 0.677, 95% CI [-0.46, 0.71]; Std. beta = 0.06, 95% CI [-0.23, 0.35])
  • The effect of attendance is statistically non-significant and negative (beta = -0.37, S.E. = 0.31, p = 0.242, 95% CI [-0.98, 0.25]; Std. beta = -0.20, 95% CI [-0.54, 0.14])
  • The effect of time point [2nd] is statistically significant and positive (beta = 1.04, S.E. = 0.46, p = 0.023, 95% CI [0.14, 1.94]; Std. beta = 0.58, 95% CI [0.08, 1.08])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: ers_e ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.10. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 12.96 (S.E. = 1.43, p < .001, 95% CI [10.16, 15.75]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -3.04e-03, S.E. = 0.02, p = 0.869, 95% CI [-0.04, 0.03]; Std. beta = -0.04, 95% CI [-0.47, 0.39])
  • The effect of gender [male] is statistically non-significant and negative (beta = -0.63, S.E. = 0.62, p = 0.310, 95% CI [-1.85, 0.59]; Std. beta = -0.56, 95% CI [-1.65, 0.52])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.04, S.E. = 0.48, p = 0.933, 95% CI [-0.98, 0.90]; Std. beta = -0.04, 95% CI [-0.87, 0.80])
  • The effect of number volunteer r is statistically significant and positive (beta = 0.43, S.E. = 0.19, p = 0.020, 95% CI [0.07, 0.80]; Std. beta = 0.34, 95% CI [0.05, 0.63])
  • The effect of attendance is statistically non-significant and negative (beta = -0.15, S.E. = 0.25, p = 0.535, 95% CI [-0.63, 0.33]; Std. beta = -0.14, 95% CI [-0.56, 0.29])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.50, S.E. = 0.28, p = 0.076, 95% CI [-0.05, 1.05]; Std. beta = 0.44, 95% CI [-0.05, 0.93])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: ers_r ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.48) and the part related to the fixed effects alone (marginal R2) is of 0.12. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 13.18 (S.E. = 1.61, p < .001, 95% CI [10.02, 16.33]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 6.87e-03, S.E. = 0.02, p = 0.739, 95% CI [-0.03, 0.05]; Std. beta = 0.06, 95% CI [-0.31, 0.44])
  • The effect of gender [male] is statistically non-significant and negative (beta = -0.84, S.E. = 0.70, p = 0.229, 95% CI [-2.21, 0.53]; Std. beta = -0.58, 95% CI [-1.53, 0.37])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.11, S.E. = 0.54, p = 0.832, 95% CI [-0.95, 1.18]; Std. beta = 0.08, 95% CI [-0.66, 0.82])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.19, S.E. = 0.28, p = 0.503, 95% CI [-0.37, 0.75]; Std. beta = 0.12, 95% CI [-0.23, 0.46])
  • The effect of attendance is statistically non-significant and negative (beta = -0.43, S.E. = 0.27, p = 0.115, 95% CI [-0.97, 0.10]; Std. beta = -0.30, 95% CI [-0.67, 0.07])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.46, S.E. = 0.44, p = 0.300, 95% CI [-0.41, 1.33]; Std. beta = 0.32, 95% CI [-0.28, 0.92])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: pss_pa ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 0.15. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 46.27 (S.E. = 4.67, p < .001, 95% CI [37.13, 55.42]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 0.03, S.E. = 0.06, p = 0.599, 95% CI [-0.09, 0.15]; Std. beta = 0.10, 95% CI [-0.28, 0.48])
  • The effect of gender [male] is statistically non-significant and negative (beta = -3.89, S.E. = 2.02, p = 0.054, 95% CI [-7.86, 0.07]; Std. beta = -0.94, 95% CI [-1.89, 0.02])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -1.11, S.E. = 1.57, p = 0.478, 95% CI [-4.19, 1.96]; Std. beta = -0.27, 95% CI [-1.01, 0.47])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.29, S.E. = 0.79, p = 0.709, 95% CI [-1.25, 1.84]; Std. beta = 0.06, 95% CI [-0.27, 0.39])
  • The effect of attendance is statistically non-significant and negative (beta = -0.35, S.E. = 0.80, p = 0.664, 95% CI [-1.91, 1.22]; Std. beta = -0.08, 95% CI [-0.46, 0.29])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.18, S.E. = 1.22, p = 0.885, 95% CI [-2.22, 2.57]; Std. beta = 0.04, 95% CI [-0.53, 0.62])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: pss_ps ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.81) and the part related to the fixed effects alone (marginal R2) is of 0.16. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 17.00 (S.E. = 8.02, p = 0.034, 95% CI [1.28, 32.72]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 5.05e-03, S.E. = 0.10, p = 0.961, 95% CI [-0.20, 0.21]; Std. beta = 0.01, 95% CI [-0.41, 0.43])
  • The effect of gender [male] is statistically non-significant and positive (beta = 2.01, S.E. = 3.49, p = 0.565, 95% CI [-4.83, 8.86]; Std. beta = 0.31, 95% CI [-0.75, 1.37])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 5.20, S.E. = 2.68, p = 0.052, 95% CI [-0.05, 10.46]; Std. beta = 0.81, 95% CI [-8.51e-03, 1.62])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -1.40, S.E. = 0.88, p = 0.110, 95% CI [-3.12, 0.32]; Std. beta = -0.19, 95% CI [-0.43, 0.04])
  • The effect of attendance is statistically non-significant and positive (beta = 1.08, S.E. = 1.38, p = 0.436, 95% CI [-1.63, 3.78]; Std. beta = 0.17, 95% CI [-0.25, 0.58])
  • The effect of time point [2nd] is statistically significant and negative (beta = -3.33, S.E. = 1.30, p = 0.010, 95% CI [-5.88, -0.79]; Std. beta = -0.52, 95% CI [-0.91, -0.12])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: pss ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 0.15. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 33.72 (S.E. = 12.03, p = 0.005, 95% CI [10.15, 57.29]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.03, S.E. = 0.16, p = 0.865, 95% CI [-0.33, 0.28]; Std. beta = -0.04, 95% CI [-0.45, 0.38])
  • The effect of gender [male] is statistically non-significant and positive (beta = 5.90, S.E. = 5.23, p = 0.260, 95% CI [-4.36, 16.16]; Std. beta = 0.60, 95% CI [-0.45, 1.66])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 6.31, S.E. = 4.03, p = 0.117, 95% CI [-1.58, 14.20]; Std. beta = 0.65, 95% CI [-0.16, 1.45])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -1.69, S.E. = 1.45, p = 0.246, 95% CI [-4.53, 1.16]; Std. beta = -0.15, 95% CI [-0.41, 0.11])
  • The effect of attendance is statistically non-significant and positive (beta = 1.42, S.E. = 2.07, p = 0.492, 95% CI [-2.63, 5.47]; Std. beta = 0.15, 95% CI [-0.27, 0.56])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -3.50, S.E. = 2.16, p = 0.106, 95% CI [-7.74, 0.74]; Std. beta = -0.36, 95% CI [-0.79, 0.08])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: rki_responsible ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.41) and the part related to the fixed effects alone (marginal R2) is of 0.26. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 17.06 (S.E. = 2.83, p < .001, 95% CI [11.52, 22.61]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.05, S.E. = 0.04, p = 0.137, 95% CI [-0.12, 0.02]; Std. beta = -0.24, 95% CI [-0.55, 0.08])
  • The effect of gender [male] is statistically non-significant and negative (beta = -2.39, S.E. = 1.22, p = 0.050, 95% CI [-4.79, 4.40e-03]; Std. beta = -0.79, 95% CI [-1.59, 1.46e-03])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.91, S.E. = 0.95, p = 0.338, 95% CI [-0.96, 2.78]; Std. beta = 0.30, 95% CI [-0.32, 0.92])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.38, S.E. = 0.58, p = 0.516, 95% CI [-1.52, 0.76]; Std. beta = -0.11, 95% CI [-0.45, 0.22])
  • The effect of attendance is statistically significant and positive (beta = 1.39, S.E. = 0.48, p = 0.004, 95% CI [0.45, 2.34]; Std. beta = 0.46, 95% CI [0.15, 0.77])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.48, S.E. = 0.94, p = 0.610, 95% CI [-2.33, 1.37]; Std. beta = -0.16, 95% CI [-0.77, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: rki_nonlinear ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.51) and the part related to the fixed effects alone (marginal R2) is of 0.09. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 12.20 (S.E. = 3.29, p < .001, 95% CI [5.75, 18.66]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.05, S.E. = 0.04, p = 0.273, 95% CI [-0.13, 0.04]; Std. beta = -0.22, 95% CI [-0.61, 0.17])
  • The effect of gender [male] is statistically non-significant and negative (beta = -0.77, S.E. = 1.43, p = 0.591, 95% CI [-3.57, 2.03]; Std. beta = -0.27, 95% CI [-1.26, 0.72])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.32, S.E. = 1.11, p = 0.775, 95% CI [-2.49, 1.85]; Std. beta = -0.11, 95% CI [-0.88, 0.66])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.31, S.E. = 0.55, p = 0.582, 95% CI [-1.39, 0.78]; Std. beta = -0.10, 95% CI [-0.44, 0.25])
  • The effect of attendance is statistically non-significant and positive (beta = 0.71, S.E. = 0.56, p = 0.207, 95% CI [-0.39, 1.81]; Std. beta = 0.25, 95% CI [-0.14, 0.64])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, S.E. = 0.86, p = 0.973, 95% CI [-1.65, 1.71]; Std. beta = 0.01, 95% CI [-0.58, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: rki_peer ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.49) and the part related to the fixed effects alone (marginal R2) is of 0.07. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 21.61 (S.E. = 2.61, p < .001, 95% CI [16.50, 26.73]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.01, S.E. = 0.03, p = 0.720, 95% CI [-0.08, 0.05]; Std. beta = -0.07, 95% CI [-0.47, 0.32])
  • The effect of gender [male] is statistically non-significant and negative (beta = -0.78, S.E. = 1.13, p = 0.492, 95% CI [-3.00, 1.44]; Std. beta = -0.35, 95% CI [-1.35, 0.65])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.12, S.E. = 0.88, p = 0.892, 95% CI [-1.60, 1.84]; Std. beta = 0.05, 95% CI [-0.72, 0.83])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.43, S.E. = 0.44, p = 0.328, 95% CI [-0.44, 1.30]; Std. beta = 0.17, 95% CI [-0.17, 0.52])
  • The effect of attendance is statistically non-significant and negative (beta = -0.32, S.E. = 0.45, p = 0.467, 95% CI [-1.20, 0.55]; Std. beta = -0.15, 95% CI [-0.54, 0.25])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.11, S.E. = 0.69, p = 0.108, 95% CI [-0.24, 2.45]; Std. beta = 0.50, 95% CI [-0.11, 1.10])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: rki_expect ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.38) and the part related to the fixed effects alone (marginal R2) is of 0.14. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 5.29 (S.E. = 1.19, p < .001, 95% CI [2.95, 7.63]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.03, S.E. = 0.02, p = 0.095, 95% CI [-0.06, 4.44e-03]; Std. beta = -0.30, 95% CI [-0.66, 0.05])
  • The effect of gender [male] is statistically non-significant and positive (beta = 0.11, S.E. = 0.52, p = 0.838, 95% CI [-0.91, 1.12]; Std. beta = 0.09, 95% CI [-0.81, 0.99])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.51, S.E. = 0.40, p = 0.206, 95% CI [-1.30, 0.28]; Std. beta = -0.45, 95% CI [-1.15, 0.25])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.03, S.E. = 0.23, p = 0.887, 95% CI [-0.49, 0.42]; Std. beta = -0.03, 95% CI [-0.39, 0.33])
  • The effect of attendance is statistically non-significant and positive (beta = 0.18, S.E. = 0.20, p = 0.367, 95% CI [-0.21, 0.58]; Std. beta = 0.16, 95% CI [-0.19, 0.52])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.27, S.E. = 0.37, p = 0.467, 95% CI [-0.46, 1.00]; Std. beta = 0.24, 95% CI [-0.41, 0.89])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: rki ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 0.29. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 56.19 (S.E. = 4.44, p < .001, 95% CI [47.49, 64.89]). Within this model:

  • The effect of age is statistically significant and negative (beta = -0.14, S.E. = 0.06, p = 0.015, 95% CI [-0.25, -0.03]; Std. beta = -0.39, 95% CI [-0.71, -0.08])
  • The effect of gender [male] is statistically significant and negative (beta = -3.82, S.E. = 1.92, p = 0.047, 95% CI [-7.59, -0.06]; Std. beta = -0.82, 95% CI [-1.63, -0.01])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.22, S.E. = 1.49, p = 0.882, 95% CI [-2.71, 3.15]; Std. beta = 0.05, 95% CI [-0.58, 0.68])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.32, S.E. = 0.86, p = 0.710, 95% CI [-2.00, 1.36]; Std. beta = -0.06, 95% CI [-0.38, 0.26])
  • The effect of attendance is statistically significant and positive (beta = 1.96, S.E. = 0.76, p = 0.009, 95% CI [0.48, 3.44]; Std. beta = 0.42, 95% CI [0.10, 0.74])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.88, S.E. = 1.37, p = 0.518, 95% CI [-1.80, 3.56]; Std. beta = 0.19, 95% CI [-0.39, 0.77])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: raq_possible ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.47) and the part related to the fixed effects alone (marginal R2) is of 0.10. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 14.63 (S.E. = 1.85, p < .001, 95% CI [11.00, 18.26]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -8.75e-03, S.E. = 0.02, p = 0.713, 95% CI [-0.06, 0.04]; Std. beta = -0.07, 95% CI [-0.45, 0.31])
  • The effect of gender [male] is statistically non-significant and negative (beta = -1.08, S.E. = 0.80, p = 0.178, 95% CI [-2.65, 0.49]; Std. beta = -0.66, 95% CI [-1.63, 0.30])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.84, S.E. = 0.62, p = 0.175, 95% CI [-0.38, 2.06]; Std. beta = 0.52, 95% CI [-0.23, 1.27])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.05, S.E. = 0.33, p = 0.872, 95% CI [-0.59, 0.69]; Std. beta = 0.03, 95% CI [-0.32, 0.38])
  • The effect of attendance is statistically non-significant and positive (beta = 0.17, S.E. = 0.32, p = 0.601, 95% CI [-0.45, 0.79]; Std. beta = 0.10, 95% CI [-0.28, 0.48])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.27, S.E. = 0.51, p = 0.593, 95% CI [-0.73, 1.27]; Std. beta = 0.17, 95% CI [-0.45, 0.78])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: raq_difficulty ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.07. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 10.59 (S.E. = 1.77, p < .001, 95% CI [7.12, 14.05]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -6.91e-03, S.E. = 0.02, p = 0.762, 95% CI [-0.05, 0.04]; Std. beta = -0.06, 95% CI [-0.47, 0.34])
  • The effect of gender [male] is statistically non-significant and negative (beta = -0.50, S.E. = 0.77, p = 0.516, 95% CI [-2.00, 1.01]; Std. beta = -0.34, 95% CI [-1.36, 0.68])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.53, S.E. = 0.59, p = 0.372, 95% CI [-0.63, 1.70]; Std. beta = 0.36, 95% CI [-0.43, 1.15])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.11, S.E. = 0.29, p = 0.714, 95% CI [-0.46, 0.67]; Std. beta = 0.06, 95% CI [-0.28, 0.41])
  • The effect of attendance is statistically non-significant and positive (beta = 0.31, S.E. = 0.30, p = 0.303, 95% CI [-0.28, 0.91]; Std. beta = 0.21, 95% CI [-0.19, 0.61])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.24, S.E. = 0.45, p = 0.589, 95% CI [-0.63, 1.12]; Std. beta = 0.16, 95% CI [-0.43, 0.76])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: raq ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 0.08. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 25.24 (S.E. = 3.53, p < .001, 95% CI [18.33, 32.15]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.02, S.E. = 0.05, p = 0.732, 95% CI [-0.10, 0.07]; Std. beta = -0.07, 95% CI [-0.47, 0.33])
  • The effect of gender [male] is statistically non-significant and negative (beta = -1.57, S.E. = 1.53, p = 0.304, 95% CI [-4.57, 1.43]; Std. beta = -0.53, 95% CI [-1.54, 0.48])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 1.39, S.E. = 1.18, p = 0.242, 95% CI [-0.94, 3.71]; Std. beta = 0.47, 95% CI [-0.32, 1.25])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.13, S.E. = 0.57, p = 0.821, 95% CI [-0.99, 1.25]; Std. beta = 0.04, 95% CI [-0.30, 0.37])
  • The effect of attendance is statistically non-significant and positive (beta = 0.48, S.E. = 0.60, p = 0.428, 95% CI [-0.71, 1.66]; Std. beta = 0.16, 95% CI [-0.24, 0.56])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.48, S.E. = 0.88, p = 0.582, 95% CI [-1.24, 2.20]; Std. beta = 0.16, 95% CI [-0.42, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: who ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.72) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 17.41 (S.E. = 5.80, p = 0.003, 95% CI [6.05, 28.78]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -0.07, S.E. = 0.07, p = 0.331, 95% CI [-0.22, 0.07]; Std. beta = -0.22, 95% CI [-0.65, 0.22])
  • The effect of gender [male] is statistically non-significant and negative (beta = -1.11, S.E. = 2.52, p = 0.661, 95% CI [-6.05, 3.84]; Std. beta = -0.25, 95% CI [-1.34, 0.85])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.85, S.E. = 1.94, p = 0.661, 95% CI [-4.66, 2.95]; Std. beta = -0.19, 95% CI [-1.03, 0.66])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.43, S.E. = 0.71, p = 0.546, 95% CI [-0.97, 1.83]; Std. beta = 0.09, 95% CI [-0.19, 0.36])
  • The effect of attendance is statistically non-significant and positive (beta = 0.16, S.E. = 1.00, p = 0.872, 95% CI [-1.79, 2.11]; Std. beta = 0.04, 95% CI [-0.40, 0.47])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.62, S.E. = 1.07, p = 0.558, 95% CI [-1.47, 2.72]; Std. beta = 0.14, 95% CI [-0.33, 0.60])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: phq ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.85) and the part related to the fixed effects alone (marginal R2) is of 0.08. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at -2.57 (S.E. = 4.96, p = 0.604, 95% CI [-12.28, 7.14]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 0.02, S.E. = 0.06, p = 0.711, 95% CI [-0.10, 0.15]; Std. beta = 0.08, 95% CI [-0.36, 0.53])
  • The effect of gender [male] is statistically non-significant and positive (beta = 0.55, S.E. = 2.16, p = 0.798, 95% CI [-3.68, 4.79]; Std. beta = 0.15, 95% CI [-0.97, 1.26])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 1.51, S.E. = 1.66, p = 0.362, 95% CI [-1.74, 4.76]; Std. beta = 0.40, 95% CI [-0.46, 1.25])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.47, S.E. = 0.46, p = 0.307, 95% CI [-1.36, 0.43]; Std. beta = -0.11, 95% CI [-0.32, 0.10])
  • The effect of attendance is statistically non-significant and positive (beta = 0.89, S.E. = 0.85, p = 0.299, 95% CI [-0.79, 2.56]; Std. beta = 0.23, 95% CI [-0.21, 0.67])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.36, S.E. = 0.67, p = 0.596, 95% CI [-1.67, 0.96]; Std. beta = -0.09, 95% CI [-0.44, 0.25])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: gad ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.83) and the part related to the fixed effects alone (marginal R2) is of 0.09. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 0.69 (S.E. = 4.11, p = 0.866, 95% CI [-7.35, 8.74]). Within this model:

  • The effect of age is statistically non-significant and negative (beta = -1.97e-03, S.E. = 0.05, p = 0.970, 95% CI [-0.11, 0.10]; Std. beta = -8.31e-03, 95% CI [-0.45, 0.43])
  • The effect of gender [male] is statistically non-significant and positive (beta = 2.37, S.E. = 1.79, p = 0.185, 95% CI [-1.13, 5.88]; Std. beta = 0.75, 95% CI [-0.36, 1.86])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.64, S.E. = 1.37, p = 0.643, 95% CI [-2.05, 3.33]; Std. beta = 0.20, 95% CI [-0.65, 1.05])
  • The effect of number volunteer r is statistically non-significant and negative (beta = -0.21, S.E. = 0.40, p = 0.592, 95% CI [-0.99, 0.57]; Std. beta = -0.06, 95% CI [-0.28, 0.16])
  • The effect of attendance is statistically non-significant and positive (beta = 0.37, S.E. = 0.71, p = 0.604, 95% CI [-1.02, 1.75]; Std. beta = 0.12, 95% CI [-0.32, 0.55])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.21, S.E. = 0.59, p = 0.717, 95% CI [-0.94, 1.36]; Std. beta = 0.07, 95% CI [-0.30, 0.43])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: nb_pcs ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 0.43. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 65.47 (S.E. = 5.62, p < .001, 95% CI [54.46, 76.48]). Within this model:

  • The effect of age is statistically significant and negative (beta = -0.29, S.E. = 0.07, p < .001, 95% CI [-0.43, -0.15]; Std. beta = -0.56, 95% CI [-0.83, -0.29])
  • The effect of gender [male] is statistically non-significant and negative (beta = -1.38, S.E. = 2.43, p = 0.570, 95% CI [-6.13, 3.38]; Std. beta = -0.20, 95% CI [-0.89, 0.49])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and positive (beta = 0.47, S.E. = 1.89, p = 0.805, 95% CI [-3.24, 4.17]; Std. beta = 0.07, 95% CI [-0.47, 0.60])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 2.11, S.E. = 1.14, p = 0.063, 95% CI [-0.12, 4.34]; Std. beta = 0.27, 95% CI [-0.02, 0.56])
  • The effect of attendance is statistically non-significant and negative (beta = -1.13, S.E. = 0.95, p = 0.236, 95% CI [-3.00, 0.74]; Std. beta = -0.16, 95% CI [-0.43, 0.11])
  • The effect of time point [2nd] is statistically significant and positive (beta = 3.98, S.E. = 1.84, p = 0.030, 95% CI [0.38, 7.58]; Std. beta = 0.58, 95% CI [0.05, 1.10])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with age, gender, previous_volunteer, number_volunteer_r, attendance and time_point (formula: nb_mcs ~ 1 + age + gender + previous_volunteer + number_volunteer_r + attendance + time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.58) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to age = 0, gender = female, previous_volunteer = yes_beyong_12_month, number_volunteer_r = 0, attendance = 0 and time_point = 1st , is at 53.24 (S.E. = 8.81, p < .001, 95% CI [35.98, 70.50]). Within this model:

  • The effect of age is statistically non-significant and positive (beta = 0.04, S.E. = 0.11, p = 0.748, 95% CI [-0.19, 0.26]; Std. beta = 0.07, 95% CI [-0.36, 0.49])
  • The effect of gender [male] is statistically non-significant and negative (beta = -2.08, S.E. = 3.82, p = 0.586, 95% CI [-9.58, 5.41]; Std. beta = -0.30, 95% CI [-1.37, 0.78])
  • The effect of previous volunteer [yes_within_12_month] is statistically non-significant and negative (beta = -0.97, S.E. = 2.95, p = 0.742, 95% CI [-6.76, 4.82]; Std. beta = -0.14, 95% CI [-0.97, 0.69])
  • The effect of number volunteer r is statistically non-significant and positive (beta = 0.18, S.E. = 1.33, p = 0.892, 95% CI [-2.42, 2.78]; Std. beta = 0.02, 95% CI [-0.31, 0.35])
  • The effect of attendance is statistically non-significant and negative (beta = -0.47, S.E. = 1.51, p = 0.755, 95% CI [-3.43, 2.49]; Std. beta = -0.07, 95% CI [-0.49, 0.36])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, S.E. = 2.02, p = 0.884, 95% CI [-4.25, 3.66]; Std. beta = -0.04, 95% CI [-0.61, 0.52])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

sets

null

3

213.008

218.494

-103.504

207.008

sets

random

9

215.734

232.191

-98.867

197.734

9.275

6

0.159

setv

null

3

184.883

190.369

-89.441

178.883

setv

random

9

188.312

204.770

-85.156

170.312

8.571

6

0.199

maks

null

3

244.500

249.986

-119.250

238.500

maks

random

9

251.844

268.302

-116.922

233.844

4.656

6

0.589

ibs

null

3

183.616

189.102

-88.808

177.616

ibs

random

9

178.206

194.664

-80.103

160.206

17.410

6

0.008

ers_e

null

3

137.551

143.037

-65.776

131.551

ers_e

random

9

142.914

159.372

-62.457

124.914

6.637

6

0.356

ers_r

null

3

164.582

170.068

-79.291

158.582

ers_r

random

9

170.849

187.306

-76.424

152.849

5.733

6

0.454

pss_pa

null

3

260.531

266.017

-127.266

254.531

pss_pa

random

9

266.211

282.669

-124.105

248.211

6.321

6

0.388

pss_ps

null

3

291.140

296.626

-142.570

285.140

pss_ps

random

9

292.449

308.906

-137.224

274.449

10.691

6

0.098

pss

null

3

330.034

335.520

-162.017

324.034

pss

random

9

334.763

351.220

-158.381

316.763

7.271

6

0.296

rki_responsible

null

3

233.777

239.263

-113.889

227.777

rki_responsible

random

9

232.629

249.086

-107.314

214.629

13.149

6

0.041

rki_nonlinear

null

3

225.935

231.421

-109.968

219.935

rki_nonlinear

random

9

233.857

250.314

-107.928

215.857

4.079

6

0.666

rki_peer

null

3

205.370

210.856

-99.685

199.370

rki_peer

random

9

213.001

229.458

-97.500

195.001

4.370

6

0.627

rki_expect

null

3

144.504

149.990

-69.252

138.504

rki_expect

random

9

149.575

166.033

-65.788

131.575

6.929

6

0.327

rki

null

3

272.479

277.965

-133.239

266.479

rki

random

9

269.921

286.379

-125.961

251.921

14.557

6

0.024

raq_possible

null

3

176.222

181.708

-85.111

170.222

raq_possible

random

9

183.728

200.185

-82.864

165.728

4.495

6

0.610

raq_difficulty

null

3

165.922

171.408

-79.961

159.922

raq_difficulty

random

9

175.121

191.579

-78.561

157.121

2.800

6

0.833

raq

null

3

229.379

234.865

-111.690

223.379

raq

random

9

237.808

254.266

-109.904

219.808

3.571

6

0.734

who

null

3

258.620

264.106

-126.310

252.620

who

random

9

268.704

285.162

-125.352

250.704

1.916

6

0.927

phq

null

3

231.097

236.583

-112.549

225.097

phq

random

9

239.559

256.017

-110.780

221.559

3.538

6

0.739

gad

null

3

217.005

222.491

-105.503

211.005

gad

random

9

224.755

241.213

-103.378

206.755

4.250

6

0.643

nb_pcs

null

3

304.857

310.343

-149.429

298.857

nb_pcs

random

9

294.631

311.089

-138.315

276.631

22.226

6

0.001

nb_mcs

null

3

306.945

312.431

-150.472

300.945

nb_mcs

random

9

317.907

334.365

-149.953

299.907

1.038

6

0.984

Post hoc analysis text

Table

outcome

time_point

n

estimate

within es

sets

1st

23

19.54 ± 3.11

sets

2nd

23

20.06 ± 3.01

-0.249

setv

1st

23

10.94 ± 2.51

setv

2nd

23

11.94 ± 2.45

-0.799

maks

1st

23

45.21 ± 5.66

maks

2nd

23

45.57 ± 5.60

-0.178

ibs

1st

23

14.66 ± 2.23

ibs

2nd

23

15.70 ± 2.18

-0.910

ers_e

1st

23

11.92 ± 1.64

ers_e

2nd

23

12.41 ± 1.61

-0.728

ers_r

1st

23

10.92 ± 2.00

ers_r

2nd

23

11.38 ± 1.95

-0.411

pss_pa

1st

23

43.43 ± 5.72

pss_pa

2nd

23

43.61 ± 5.59

-0.058

pss_ps

1st

23

25.74 ± 8.93

pss_ps

2nd

23

22.41 ± 8.83

1.065

pss

1st

23

45.31 ± 13.60

pss

2nd

23

41.81 ± 13.42

0.668

rki_responsible

1st

23

21.18 ± 3.76

rki_responsible

2nd

23

20.70 ± 3.65

0.197

rki_nonlinear

1st

23

13.28 ± 4.03

rki_nonlinear

2nd

23

13.31 ± 3.94

-0.014

rki_peer

1st

23

19.29 ± 3.21

rki_peer

2nd

23

20.40 ± 3.13

-0.642

rki_expect

1st

23

4.95 ± 1.55

rki_expect

2nd

23

5.22 ± 1.50

-0.283

rki

1st

23

58.73 ± 5.73

rki

2nd

23

59.62 ± 5.57

-0.252

raq_possible

1st

23

15.04 ± 2.30

raq_possible

2nd

23

15.32 ± 2.25

-0.212

raq_difficulty

1st

23

12.01 ± 2.15

raq_difficulty

2nd

23

12.25 ± 2.10

-0.217

raq

1st

23

27.07 ± 4.26

raq

2nd

23

27.55 ± 4.17

-0.221

who

1st

23

14.43 ± 6.58

who

2nd

23

15.05 ± 6.49

-0.241

phq

1st

23

3.89 ± 5.41

phq

2nd

23

3.53 ± 5.37

0.222

gad

1st

23

3.93 ± 4.51

gad

2nd

23

4.14 ± 4.47

-0.151

nb_pcs

1st

23

47.89 ± 7.41

nb_pcs

2nd

23

51.87 ± 7.19

-0.837

nb_mcs

1st

23

50.87 ± 10.43

nb_mcs

2nd

23

50.57 ± 10.23

0.059

Plot